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NEW Feature

This repo is adapted based on the original LVI_SAM, which makes it easier to adapt your sensor.

  1. We have improved the global consitency of the previous SLAM systems. The tightly coupled lio slam system lacks global consistency because of its lack of front-end. Refer to the back-end part of lio_sam and connect to GTSAM for back-end optimization.

  2. The original version of lio_sam sets many sensor external parameters to fixed values in the code, this version extracts the external parameters into the yaml file, making it easier to configure;

  3. The original version of lio_sam dose not consider the translation amount between lidar and camera, this version adds the translation amount;

  4. The "imu2LidarExtrinsicRotation" 、“extrinsicRotation”、“extrinsicTranslation”、"lcExtrinsicRotation" and "lcExtrinsicTranslation" in "config/params_camera.yaml" needs to be set as your device extrinsic.

This repository contains code for a lidar-visual-inertial odometry and mapping system, which combines the advantages of LIO-SAM and Vins-Mono at a system level.

Dependency

  • ROS (Tested with kinetic and melodic)
  • gtsam (Georgia Tech Smoothing and Mapping library) 
    sudo add-apt-repository ppa:borglab/gtsam-release-4.0
sudo apt install libgtsam-dev libgtsam-unstable-dev
  • Ceres (C++ library for modeling and solving large, complicated optimization problems) 
    sudo apt-get install -y libgoogle-glog-dev
sudo apt-get install -y libatlas-base-dev
wget -O ~/Downloads/ceres.zip https://github.com/ceres-solver/ceres-solver/archive/1.14.0.zip
cd ~/Downloads/ && unzip ceres.zip -d ~/Downloads/
cd ~/Downloads/ceres-solver-1.14.0
mkdir ceres-bin && cd ceres-bin
cmake ..
sudo make install -j4

Getting start with Docker

When you use Docker, you could solve the dependency at once.
For more information, you can check docker_start.md.

Compile

You can use the following commands to download and compile the package.

cd ~/catkin_ws/src
git clone https://github.com/TixiaoShan/LVI-SAM.git
cd ..
catkin_make

Datasets

The datasets used in the paper can be downloaded from Google Drive. The data-gathering sensor suite includes: Velodyne VLP-16 lidar, FLIR BFS-U3-04S2M-CS camera, MicroStrain 3DM-GX5-25 IMU, and Reach RS+ GPS.

https://drive.google.com/drive/folders/1q2NZnsgNmezFemoxhHnrDnp1JV_bqrgV?usp=sharing

Note that the images in the provided bag files are in compressed format. So a decompression command is added at the last line of launch/module_sam.launch. If your own bag records the raw image data, please comment this line out.

Run the package

  1. Configure parameters:
Configure sensor parameters in the .yaml files in the ```config``` folder.
  1. Run the launch file:
roslaunch lvi_sam run.launch
  1. Play existing bag files:
rosbag play handheld.bag

Related Packages

TODO

  • Update graph optimization using all three factors in imuPreintegration.cpp, simplify mapOptimization.cpp, increase system stability